After running a multiple regression on sample of 124 students in a university, following results are generated. log(Y) = 0.01 + 0.3 X1 – 0.11 log(X2) + 0.03 log (X3) + E se = t = R2 = 0.65 %3D (0.06) ( ) (0.2) (0.001) (2.4) Where; Y = Students CGPA X1 = family income in 1,000 X2 = Number of subjects enrolled X3 = hours spent on studying Required: (a) Which of independent variables are statistically significant at 0.05? (b) Would you reject the null hypothesis that number of subjects enrolled has no effect or whatsoever on students CGPA? (c) What is the overall significance of the regression at the 5 percent level? State the hypotheses and show the necessary calculations. What can you conclude?
After running a multiple regression on sample of 124 students in a university, following results are generated. log(Y) = 0.01 + 0.3 X1 – 0.11 log(X2) + 0.03 log (X3) + E se = t = R2 = 0.65 %3D (0.06) ( ) (0.2) (0.001) (2.4) Where; Y = Students CGPA X1 = family income in 1,000 X2 = Number of subjects enrolled X3 = hours spent on studying Required: (a) Which of independent variables are statistically significant at 0.05? (b) Would you reject the null hypothesis that number of subjects enrolled has no effect or whatsoever on students CGPA? (c) What is the overall significance of the regression at the 5 percent level? State the hypotheses and show the necessary calculations. What can you conclude?
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 2TI: Sales of a video game released in the year 2000 took off at first, but then steadily slowed as time...
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Transcribed Image Text:After running a multiple regression on sample of 124 students in a university, following
results are generated.
log(Y) = 0.01 + 0.3 X1 – 0.11 log(X2) + 0.03 log (X3) + ɛ
(0.06)
( )
(2.4)
se =
(0.2)
(0.001)
R2 = 0.65
Where;
Y = Students CGPA
Xi = family income in 1,000
X2 = Number of subjects enrolled
X3 = hours spent on studying
Required:
(a)
Which of independent variables are statistically significant at 0.05?
(b) Would you reject the null hypothesis that number of subjects enrolled has no effect
or whatsoever on students CGPA?
(c)
What is the overall significance of the regression at the 5 percent level? State the
hypotheses and show the necessary calculations. What can you conclude?
(d) Can you interpret the coefficients of X1 and X2 as elasticity coefficients? Why or why
not?
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